How to Set Profit Targets and Control Losses: Statistical Analysis Can Be Used to Collect the Data Needed to Build a Proper Risk Management Framework. Here, We Show How to Apply It-And Discuss the Lessons Learned

By Rosenthal, Neil | Futures (Cedar Falls, IA), December 2012 | Go to article overview

How to Set Profit Targets and Control Losses: Statistical Analysis Can Be Used to Collect the Data Needed to Build a Proper Risk Management Framework. Here, We Show How to Apply It-And Discuss the Lessons Learned


Rosenthal, Neil, Futures (Cedar Falls, IA)


In the first installment of this series, we introduced a random entry system that based its entries on a virtual coin flip (see "Guide to trading system development," September 2012). The base system was backtested across four years of euro forex data to gather trade data for statistical analysis. As we saw, the base system was unprofitable. In mathematical terms, the base system has a negative expectancy of -0.81.

Expectancy is an important metric. It is the amount you can expect to win or lose for every dollar risked. It is calculated with the following formula:

(Winning percentage x Average win) - (Losing percentage x Average loss)

That is, the system loses 81C for every dollar risked. The astute reader likely recognized this aspect of the system as a stumbling block that often trips up the beginning system trader: It is unlikely, if not impossible, that a system with a negative expectancy can be made profitable through trade management. As it turns out, this system is unprofitable regardless of any stop loss or profit target that may be added.

This does not mean the system necessarily should be discarded. It often is the case that, though the first version fails, an adjustment to some aspect of it may result in a profitable system. In this case, there is another parameter of our demonstration system that can be adjusted: The entry time.

The 8 a.m. (EST) entry was chosen arbitrarily. This may be the critical variable that can salvage our model and allow system development to proceed. Indeed, this turns out to be the case. A simple optimization of the entry time (stepping from 3 a.m., EST, the London open, through 8 a.m., EST, in one-hour increments) creates a profitable system. When backtested across the same data, an entry time of 4 a.m. produces a net profit of $2,853. Expectancy is a positive 2.75. Now we can apply trade management techniques to see if we can improve the results.

Walk-forward analysis

If a system is backtested across an entire historical data series, the results of such tests will indicate only how the system would have fared had it been operational during the time period covered by the historical data. The results tell us nothing about how the system will fare going forward in real time.

One way to address this limitation is walk-forward analysis and optimization, popularized within the trading community by Robert Pardo. With this approach, the historical data are broken up into smaller periods of time. The system then can be backtested and optimized against just a portion of data, called the in-sample data. After the system parameters have been optimized, it then can be tested on the portion of the data that immediately follows, or the out-of-sample data.

The out-of-sample data period usually is a percentage of the in-sample data period. The results of the out-of-sample tests are recorded. The process then is repeated by "sliding forward" the in-sample data period and then re-optimizing the parameters. The amount by which the in-sample data is slid forward is equal to the length of the initial out-of-sample data period (see "Walk-forward testing," right).

In the chart, the in-sample data period is six months and the out-of-sample data period is two months. The first optimization is run on the data from January through June. The test is run on the data from July through August. The out-of-sample results are recorded. The in-sample data period then slides forward by two months. A new optimization is run and the parameters are re-set accordingly. Another out-of-sample test is run September through October.

This walk forward through the data removes some of the limitations of basic backtesting. Profitable results from this method of testing should provide a higher level of confidence in the system when traded in real time in a live account.

Setting our stop

The next phase of development of the trading system is to add risk management in the form of the initial stop loss (ISL). …

The rest of this article is only available to active members of Questia

Already a member? Log in now.

Notes for this article

Add a new note
If you are trying to select text to create highlights or citations, remember that you must now click or tap on the first word, and then click or tap on the last word.
One moment ...
Default project is now your active project.
Project items

Items saved from this article

This article has been saved
Highlights (0)
Some of your highlights are legacy items.

Highlights saved before July 30, 2012 will not be displayed on their respective source pages.

You can easily re-create the highlights by opening the book page or article, selecting the text, and clicking “Highlight.”

Citations (0)
Some of your citations are legacy items.

Any citation created before July 30, 2012 will labeled as a “Cited page.” New citations will be saved as cited passages, pages or articles.

We also added the ability to view new citations from your projects or the book or article where you created them.

Notes (0)
Bookmarks (0)

You have no saved items from this article

Project items include:
  • Saved book/article
  • Highlights
  • Quotes/citations
  • Notes
  • Bookmarks
Notes
Cite this article

Cited article

Style
Citations are available only to our active members.
Buy instant access to cite pages or passages in MLA, APA and Chicago citation styles.

(Einhorn, 1992, p. 25)

(Einhorn 25)

1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

Cited article

How to Set Profit Targets and Control Losses: Statistical Analysis Can Be Used to Collect the Data Needed to Build a Proper Risk Management Framework. Here, We Show How to Apply It-And Discuss the Lessons Learned
Settings

Settings

Typeface
Text size Smaller Larger Reset View mode
Search within

Search within this article

Look up

Look up a word

  • Dictionary
  • Thesaurus
Please submit a word or phrase above.
Print this page

Print this page

Why can't I print more than one page at a time?

Help
Full screen

matching results for page

    Questia reader help

    How to highlight and cite specific passages

    1. Click or tap the first word you want to select.
    2. Click or tap the last word you want to select, and you’ll see everything in between get selected.
    3. You’ll then get a menu of options like creating a highlight or a citation from that passage of text.

    OK, got it!

    Cited passage

    Style
    Citations are available only to our active members.
    Buy instant access to cite pages or passages in MLA, APA and Chicago citation styles.

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn, 1992, p. 25).

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn 25)

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences."1

    1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

    Cited passage

    Thanks for trying Questia!

    Please continue trying out our research tools, but please note, full functionality is available only to our active members.

    Your work will be lost once you leave this Web page.

    Buy instant access to save your work.

    Already a member? Log in now.

    Oops!

    An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.